Comparar métodos

	Pareamiento por Puntuación de Propensión en Investigación Educativa	Ponderación por Probabilidad Inversa de Tratamiento (IPW / IPTW)
Campo	Inferencia causal	Inferencia causal
Familia	Regression model	Regression model
Año de origen	1983 (foundational); education adoption widespread from late 1990s	2000
Autor original	Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002)	Robins, Hernán & Brumback
Tipo	Quasi-experimental / matching-based causal inference	Causal inference weighting estimator
Fuente seminal	Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55.	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560.
Alias	PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching education	IPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Relacionados	5	5
Resumen	Propensity Score Matching (PSM) in education research is a quasi-experimental technique that creates comparable treatment and control groups from observational student, teacher, or school data. By balancing groups on observed background characteristics, it enables credible causal estimates of educational interventions — such as tutoring programs, school choice policies, or teacher professional development — when random assignment is infeasible.	Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.